165 research outputs found

    Arbitrarily large neutron amplification in subcritical nuclear reactors

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    Gaussian continuous tensor network states for simple bosonic field theories

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    Preprint arXiv: 2209.11253 Submitted on 22 Sep 2022

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    We study the interplay between symmetry representations of the physical and virtual space on the class of tensor network states for critical spins systems known as field tensor network states (fTNS). These are by construction infinite dimensional tensor networks whose virtual space is described by a conformal field theory (CFT). We can represent a symmetry on the physical index as a commutator with the corresponding CFT current on the virtual space. By then studying this virtual space representation we can learn about the critical symmetry protected topological properties of the state, akin to the classification of symmetry protected topological order for matrix product states. We use this to analytically derive the critical symmetry protected topological properties of the two ground states of the Majumdar-Ghosh point with respect to the previously defined symmetries

    The Tension on dsDNA Bound to ssDNA/RecA Filaments May Play an Important Role in Driving Efficient and Accurate Homology Recognition and Strand Exchange

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    It is well known that during homology recognition and strand exchange the double stranded DNA (dsDNA) in DNA/RecA filaments is highly extended, but the functional role of the extension has been unclear. We present an analytical model that calculates the distribution of tension in the extended dsDNA during strand exchange. The model suggests that the binding of additional dsDNA base pairs to the DNA/RecA filament alters the tension in dsDNA that was already bound to the filament, resulting in a non-linear increase in the mechanical energy as a function of the number of bound base pairs. This collective mechanical response may promote homology stringency and underlie unexplained experimental results

    On the Regression and Assimilation for Air Quality Mapping Using Dense Low-Cost WSN

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    International audienceThe use of low-cost Wireless Sensor Networks (WSNs) for air quality monitoring has recently attracted a great deal of interest. Indeed, the cost-effectiveness of emerging sensors and their small size allow for dense deployments and hence improve the spatial granularity. However, these sensors offer a low accuracy and their measurement errors may be significant due to the underlying sensing technologies. The main aim of this work is to reconsider and compare some regression approaches to assimilation ones while taking into account the intrinsic characteristics of dense deployment of low cost WSN for air quality monitoring (high density, numerical model errors and sensing errors). For that, we propose a general framework that allows the comparison of different strategies based on numerical simulations and an adequate estimation of the simulation error covariances as well as the sensing errors covariances. While considering the case of Lyon city and a widely used numerical model, we characterize the simulation errors, conduct extensive simulations and compare several regression and assimilation approaches. The results show that from a given sensing error threshold, regression methods present an optimal sensor density from which the mapping quality decreases. Results also show that the Random Forest method is often the best regression approach but still less efficient than the BLUE assimilation approach when using adequate correction parameters

    Logical Development of the Cell Ontology

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    <p>Abstract</p> <p>Background</p> <p>The Cell Ontology (CL) is an ontology for the representation of <it>in vivo </it>cell types. As biological ontologies such as the CL grow in complexity, they become increasingly difficult to use and maintain. By making the information in the ontology computable, we can use automated reasoners to detect errors and assist with classification. Here we report on the generation of computable definitions for the hematopoietic cell types in the CL.</p> <p>Results</p> <p>Computable definitions for over 340 CL classes have been created using a genus-differentia approach. These define cell types according to multiple axes of classification such as the protein complexes found on the surface of a cell type, the biological processes participated in by a cell type, or the phenotypic characteristics associated with a cell type. We employed automated reasoners to verify the ontology and to reveal mistakes in manual curation. The implementation of this process exposed areas in the ontology where new cell type classes were needed to accommodate species-specific expression of cellular markers. Our use of reasoners also inferred new relationships within the CL, and between the CL and the contributing ontologies. This restructured ontology can be used to identify immune cells by flow cytometry, supports sophisticated biological queries involving cells, and helps generate new hypotheses about cell function based on similarities to other cell types.</p> <p>Conclusion</p> <p>Use of computable definitions enhances the development of the CL and supports the interoperability of OBO ontologies.</p

    Recognition of vitamin B metabolites by mucosal-associated invariant T cells

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    The mucosal-associated invariant T-cell antigen receptor (MAIT TCR) recognizes MR1 presenting vitamin B metabolites. Here we describe the structures of a human MAIT TCR in complex with human MR1 presenting a non-stimulatory ligand derived from folic acid and an agonist ligand derived from a riboflavin metabolite. For both vitamin B antigens, the MAIT TCR docks in a conserved manner above MR1, thus acting as an innate-like pattern recognition receptor. The invariant MAIT TCR a-chain usage is attributable to MR1-mediated interactions that prise open the MR1 cleft to allow contact with the vitamin B metabolite. Although the non-stimulatory antigen does not contact the MAIT TCR, the stimulatory antigen does. This results in a higher affinity of the MAIT TCR for a stimulatory antigen in comparison with a non-stimulatory antigen. We formally demonstrate a structural basis for MAIT TCR recognition of vitamin B metabolites, while illuminating how TCRs recognize microbial metabolic signatures

    Clonal selection in the human Vδ1 T cell repertoire indicates γδ TCR-dependent adaptive immune surveillance

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    γδ T cells are considered to be innate-like lymphocytes that respond rapidly to stress without clonal selection and differentiation. Here we use next-generation sequencing to probe how this paradigm relates to human Vδ2neg T cells, implicated in responses to viral infection and cancer. The prevalent Vδ1 T cell receptor (TCR) repertoire is private and initially unfocused in cord blood, typically becoming strongly focused on a few high-frequency clonotypes by adulthood. Clonal expansions have differentiated from a naive to effector phenotype associated with CD27 downregulation, retaining proliferative capacity and TCR sensitivity, displaying increased cytotoxic markers and altered homing capabilities, and remaining relatively stable over time. Contrastingly, Vδ2+ T cells express semi-invariant TCRs, which are present at birth and shared between individuals. Human Vδ1+ T cells have therefore evolved a distinct biology from the Vδ2+ subset, involving a central, personalized role for the γδ TCR in directing a highly adaptive yet unconventional form of immune surveillance

    MAIT cells launch a rapid, robust and distinct hyperinflammatory response to bacterial superantigens and quickly acquire an anergic phenotype that impedes their cognate antimicrobial function: Defining a novel mechanism of superantigen-induced immunopathology and immunosuppression

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    Superantigens (SAgs) are potent exotoxins secreted by Staphylococcus aureus and Streptococcus pyogenes. They target a large fraction of T cell pools to set in motion a "cytokine storm" with severe and sometimes life-threatening consequences typically encountered in toxic shock syndrome (TSS). Given the rapidity with which TSS develops, designing timely and truly targeted therapies for this syndrome requires identification of key mediators of the cytokine storm's initial wave. Equally important, early host responses to SAgs can be accompanied or followed by a state of immunosuppression, which in turn jeopardizes the host's ability to combat and clear infections. Unlike in mouse models, the mechanisms underlying SAg-associated immunosuppression in humans are ill-defined. In this work, we have identified a population of innate-like T cells, called mucosa-associated invariant T (MAIT) cells, as the most powerful source of pro-inflammatory cytokines after exposure to SAgs. We have utilized primary human peripheral blood and hepatic mononuclear cells, mouse MAIT hybridoma lines, HLA-DR4-transgenic mice, MAIThighHLA-DR4+ bone marrow chimeras, and humanized NOD-scid IL-2Rγnull mice to demonstrate for the first time that: i) mouse and human MAIT cells are hyperresponsive to SAgs, typified by staphylococcal enterotoxin B (SEB); ii) the human MAIT cell response to SEB is rapid and far greater in magnitude than that launched by unfractionated conventional T, invariant natural killer T (iNKT) or γδ T cells, and is characterized by production of interferon (IFN)-γ, tumor necrosis factor (TNF)-α and interleukin (IL)-2, but not IL-17A; iii) high-affinity MHC class II interaction with SAgs, but not MHC-related protein 1 (MR1) participation, is required for MAIT cell activation; iv) MAIT cell responses to SEB can occur in a T cell receptor (TCR) Vβ-specific manner but are largely contributed by IL-12 and IL-18; v) as MAIT cells are primed by SAgs, they also begin to develop a molecular signature consistent with exhaustion and failure to participate in antimicrobial defense. Accordingly, they upregulate lymphocyte-activation gene 3 (LAG-3), T cell immunoglobulin and mucin-3 (TIM-3), and/or programmed cell death-1 (PD-1), and acquire an anergic phenotype that interferes with their cognate function against Klebsiella pneumoniae and Escherichia coli; vi) MAIT cell hyperactivation and anergy co-utilize a signaling pathway that is governed by p38 and MEK1/2. Collectively, our findings demonstrate a pathogenic, rather than protective, role for MAIT cells during infection. Furthermore, we propose a novel mechanism of SAg-associated immunosuppression in humans. MAIT cells may therefore provide an attractive therapeutic target for the management of both early and late phases of severe SAg-mediated illnesses
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